Text Classification
Transformers
PyTorch
Safetensors
English
roberta
emotions
multi-class-classification
multi-label-classification
text-embeddings-inference
Instructions to use SamLowe/roberta-base-go_emotions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamLowe/roberta-base-go_emotions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SamLowe/roberta-base-go_emotions") model = AutoModelForSequenceClassification.from_pretrained("SamLowe/roberta-base-go_emotions", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SamLowe/roberta-base-go_emotions: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/SamLowe/roberta-base-go_emotions/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SamLowe/roberta-base-go_emotions/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SamLowe/roberta-base-go_emotions/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- e443a993e6371cc8ab720171858f131ca53c36a5368406718144716e1d0bd04d
- Size of remote file:
- 499 MB
- SHA256:
- 4fd088956d38ce7ca956815b0203caf6f29b492b04c22c50d67542b3e02c449d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.